3 papers
cs.LG2026
Linear Mode Connectivity under Data Shifts for Deep Ensembles of Image Classifiers
C. Hepburn, T. Zielke, A. P. Raulf
The phenomenon of linear mode connectivity (LMC) links several aspects of deep learning, including training stability under noisy stochastic gradients, the smoothness and generaliz…
cs.LG2026
Robustness and Regularization in Hierarchical Re-Basin
Benedikt Franke, Florian Heinrich, Markus Lange +1
This paper takes a closer look at Git Re-Basin, an interesting new approach to merge trained models. We propose a hierarchical model merging scheme that significantly outperforms t…
cs.LG2025
On Advancements of the Forward-Forward Algorithm
Mauricio Ortiz Torres, Markus Lange, Arne P. Raulf
The Forward-Forward algorithm has evolved in machine learning research, tackling more complex tasks that mimic real-life applications. In the last years, it has been improved by se…